Point of View

Reimagining asset optimization in the age of the industrial internet

Explore

The Internet of Things (IoT) is changing everything and has the potential to transform asset performance in industries that usually have very large legacy asset bases. Significant investments are predicted, considering the potential of the interplay between new technologies and legacy processes, assets and systems. Genpact studies have found that a $1-billion industrial service business often incurs $80 to $100 million in missed revenue and up to $15 million in lost profits due to lack of visibility and understanding of industrial assets under contract.

Industrial solutions that generate step-change impact

Advanced digital technologies allow for the storage and processing of vast amounts of structured and unstructured data. But the key doesn't only lie in storing more data. The volume and attributes of data generated by industrial machinery and the problems it can be applied to present unique challenges.

The solution framework must start with the business problems that industrial machinery organizations are trying to solve and work backward to the actions, people and—finally—data that is required.

Avoiding data 'swamps'

The overflow of data streams can easily turn, for lack of a better term, into swamps—large legacy environments that are hard to manage and expensive to keep. Reimagination of industrial solutions must focus on the plumbing that combines usable, relevant data together and takes it through analytical engines that deliver actionable insights. Then, the loop must be closed through operational and engineering processes—at scale.

The final outcome can create a host of benefits, such as pricing aftermarket service contracts more intelligently and winning profitable contracts. Other advantages include enhancing asset uptime and delighting the client, as well as ensuring sustainable profit margins by predicting and limiting factors driving cost variance. Just as importantly, a fully reimagined process allows industry to engineer better, more reliable products in the future. Lean management practices can help overcome the inertia of legacy, change management and transformation cost.

An example from the power world

A case in point is a leader in distributed power. Struggling with high maintenance costs, decreasing profitability and falling client satisfaction, its asset performance management program ensured intelligent scheduling of preventive maintenance and standardization of maintenance processes.

We used a cloud platform for the industrial internet which helped standardize and automate the scheduling, workflow and monitoring of routine, corrective and engine change maintenance work.

The business impact is lower maintenance costs and asset downtime resulting in higher profits.

Lean DigitalSM and Intelligent OperationsSM

Seamlessly integrating and analyzing performance and health data with supporting business systems using advanced industrial internet platforms offers insights into critical industrial assets. This ability to provide a critical link between assets and business functions aligns with Genpact’s vision of leveraging Lean practices for digital processes. The advantage of designing and optimizing the full Data-to-Insight-to-Action arc is significant, especially when continuous learning and feedback from operations can now be crystallized into powerful analytical platforms. The resulting ability to collect and use more meaningful data leads to increased revenue and accurate cost forecasting across multiple asset performance scenarios. This can be a considerable competitive weapon for manufacturers with a significant installed base or for those who can source more data from the machinery their clients deploy.

Take a copy for yourself

Download PDF

An industrial asset optimization portfolio that enhances asset uptime and reduces revenue leakage and service costs

Such operations are clearly different from traditional ones. Genpact calls these operations “intelligent” because they leverage analytics as an integral component of the business process. As a result, they can better sense and react to operational conditions (such as asset usage patterns or new field operations constraints) and learn from those data sets. In turn, those important business processes can run continuously and more effectively. The business impact is millions of dollars of enterprise value for the manufacturer and their clients, as well as radically superior controllership and auditability of complex, global operations.